Some U.S. states have more difficulty than others in recruiting or retaining dentists. Part of the problem is that often dental students are not aware of opportunities across geographic regions of either their home state or the state where they were educated. With student input, the University of Iowa College of Dentistry and Dental Clinics designed and launched an interactive website that provides basic demographic, economic, and other meaningful information to help dental students locate potential practice locations and identify current employment opportunities in Iowa. Although this website is not a recruitment or retention panacea, it provides an easy method for dental students to explore all or parts of the state as they go about making one of the most important decisions of their careers. The website also provides a showcase for current practitioners and communities to demonstrate what they have to offer as practice opportunities.
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BMC Oral Health
January 2025
Department of Removable Prosthodontics, School of Dentistry, Aichi Gakuin University, 2-11 Suemori- dori, Chikusa-ku, Nagoya, Aichi, 464-8651, Japan.
Background: When designing removable partial dentures, maximizing the effectiveness of support and bracing is necessary to minimize denture movement. Therefore, it is essential to emphasize the importance of providing patients with appropriate, safe, and secure removable partial dentures and have clinicians rerecognize the concept and importance of support and bracing. This study aimed to present extension-base removable partial dentures through six specific clinical case series and describe the effect of support and bracing action on denture design, which is essential for denture movement minimization.
View Article and Find Full Text PDFBMC Med Educ
January 2025
La Trobe Rural Health School, La Trobe University, Bendigo, VIC, 3550, Australia.
Background: Most research on tracking practice locations of health students has focused on medical students, particularly the factors influencing their choice to work in rural and remote areas. However, there is limited research on how rural origin and training in regional or rural settings affect the employment destinations of dental and oral health graduates. This paper explores the practice locations of dentistry and oral health therapy (OHT) graduates from rural backgrounds compared to those from metropolitan areas in Australia.
View Article and Find Full Text PDFPLoS One
January 2025
Faculty of Dentistry, PHENIKAA University, Hanoi, Vietnam.
Objectives: This study aims to evaluate the performance of the latest large language models (LLMs) in answering dental multiple choice questions (MCQs), including both text-based and image-based questions.
Material And Methods: A total of 1490 MCQs from two board review books for the United States National Board Dental Examination were selected. This study evaluated six of the latest LLMs as of August 2024, including ChatGPT 4.
Eur J Dent Educ
January 2025
Department of Prosthodontics, New York University College of Dentistry, New York, New York, USA.
Introduction: Objective Structured Clinical Examinations (OSCEs) serve as a reliable assessment tool for clinical and competency evaluation. Traditional OSCEs, involving live patients, present logistical challenges and evoke student anxiety. In an effort to create a comprehensive clinical series of examinations, electronic OSCEs (e-OSCEs) were developed for assessing clinical competencies in prosthodontics at a large dental school.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Bangkok Hospital Dental Center Holistic Care and Dental Implant, Bangkok Hospital, Bangkok, 10310, Thailand.
Background: Assessing the difficulty of impacted lower third molar (ILTM) surgical extraction is crucial for predicting postoperative complications and estimating procedure duration. The aim of this study was to evaluate the effectiveness of a convolutional neural network (CNN) in determining the angulation, position, classification and difficulty index (DI) of ILTM. Additionally, we compared these parameters and the time required for interpretation among deep learning (DL) models, sixth-year dental students (DSs), and general dental practitioners (GPs) with and without CNN assistance.
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